Data Scientist - Lead Gen

Position Summary

Are you passionate about turning data into revenue? Join Purpose Financial's fast-growing Lead Generation team, where data scientists play a central role in driving customer acquisition strategy across credit-based channels. This position reports to the Director, Data Science – Lead Generation and supports the data science strategy powering ping tree and offer wall-based consumer loan acquisition. This role contributes to lead scoring, routing, experimentation, and performance optimization to drive profitable growth across third-party acquisition channels.

Job Responsibility

• Develop data science strategy for ping tree and offer wall lead generation
• Build and maintain models predicting conversion, approval, funding, loss, and lifetime value across acquisition funnels
• Build and maintain lead scoring models to prioritize high-quality acquisition leads
• Support real-time lead valuation, routing, and acceptance logic
• Design and execute A/B tests across acquisition funnels to improve model accuracy and business outcomes
• Automate data pipelines, reporting, and analysis to drive efficiency and provide actionable insights
• Develop processes to cleanse, integrate, and evaluate large, diverse datasets to derive insight into consumer financial behavior
• Evaluate new lead sources and traffic types in partnership with Marketing
• Perform ad-hoc analyses to support strategic decision-making and business initiatives
• Ensure compliance with company policies and industry regulations
• Collaborate closely with Marketing, Credit Risk, Engineering, and Operations teams

Accountability

Understand, adhere to, and enforce all corporate policies. 

Job Responsibilities Cont.

Education Required

Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, or related disciplines (Advanced degree preferred).

Experience Required

• 2+ years of experience in data science or a related field, with a focus on attributable digital lead generation or customer acquisition.
• Proactive and self-driven with a strong sense of ownership — takes initiative, follows through, and holds themselves accountable for outcomes
• Experience with credit-based customer acquisition strategies, lead generation models, and marketing analytics in the financial services or consumer lending industry
• Proficiency in machine learning techniques and Python libraries (Pandas, scikit-learn, XGBoost, SHAP), with hands-on experience building and deploying machine learning models using Python or R
• Proficiency in SQL for data manipulation and analysis
• Proficiency in reporting tools such as Tableau or Power BI
• Comfortable solving complex problems using higher-level mathematics; ability to combine data from multiple sources and interpret business performance
• Excellent communication skills, both written and verbal, to communicate in person, by phone, and through email
• Flexibility to adapt to a dynamic, fast-paced environment with changing priorities

Knowledge Required

Excellent written and verbal communications skills; adaptability and flexibility to a changing environment; and comfortable working in a dynamic, high volume, fast-paced environment. Ability to understand and ensure compliance with policies, procedures, and laws governing our industry/business and products.

Physical Requirements

Sitting for long periods of time; standing occasionally; walking; bending; squatting; kneeling; pushing/pulling; reaching; twisting; frequent lifting of less than 10 lbs., occasional lifting of up to 20 lbs.; driving and having access during the workday to an insured and reliable transportation; typing; data entry; grasping; transferring items between hands and/or to another person or receptacle; use of office equipment to include computers; ability to travel to, be physically present at, and complete the physical requirements of the position at any assigned location.

Competencies

Travel

up to 5%

Attire

Business Casual

Other

Must be eligible to work in the USA and able to pass a background check.